How can you improve web analytics data quality?

In my experience, this is crucial to define your goals and KPIs. Far too often, the deluge of data ensures that you will end up making dashboards which shall keep hitting your inboxes daily, but which will lose its significance fast. The filter I use to arrive at a metric ( KPI ) which matters is - is this information which matters to me daily ? Is this information going to give me some actionable to chase? A quick honest answer to these two questions shall help in keeping your lives simple and focused on the metrics which matter in web analytics.

1st, implement filters to exclude internal traffic, spam, and other irrelevant data. This will provide a more accurate representation of user behavior and engagement on your website. 2nd, conduct periodic audits of your tracking codes to identify any broken or outdated tags. Make sure all the required tracking elements are working.

Before diving into data collection and analysis, adopt a holistic approach by envisioning the business as a cohesive unit. Begin with a 'north star' objective and employ a KPI tree structure. This model breaks down your overarching goal into smaller, actionable KPIs for campaigns, channels, and your website. By aligning data efforts with this strategic framework, you gain a comprehensive understanding of your business and its interdependencies, empowering informed decision-making across your organization.

Consider exploring website analytics audit checklists, readily available across the internet. Keep in mind that achieving flawless tracking is challenging. Striking a balance between comprehensive tracking and time invested is essential. Aim to prevent critical errors and ensure the acquisition of accurate, organized data.

While filtering out undesirable traffic remains crucial, preserving the raw data and maintaining an untouched version can also be valuable.

Discrepancies can arise between web analytics data from tools like Google Analytics or Adobe Analytics and a company's CRM system. These disparities might result from web analytics tags not being triggered in all instances, often due to ad-blockers and similar factors. It's common to expect a normal discrepancy of around 5-8%. However, if the gap is larger, further investigation is warranted.

Traffic data is essential for any successful digital marketing campaign. Figuring out my engaged audience is essential. Benenfits include : - Customized content based on previous activity - Ability to build a funnel that tracks the visitors journey from start (Website visit) to finish (Purchase) Many other benefits come from accurate tracking such as optimising website flow and reducing bounce rate ..etc. Finally, you cannot expect to have a profitable website without installing the Facebook Pixel or Google Tracking tag

Enhancing web analytics data quality is crucial for informed decisions. Start by accurately implementing tracking codes, then audit sources regularly, employ filters, and respect user privacy preferences. Update analytics configurations with site changes, cross-reference data, and invest in employee training for a robust data-driven approach.